In this paper we examine the application of the random forest classifier for the all relevant feature selection problem. To this end we first examine two recently proposed all relevant feature selection algorithms, both being a random forest wrappers, on a series of synthetic data sets with varying size. We show that reasonable accuracy of predictions can be achieved and that heuristic algorith...

Abstract Moral influence theories of responsibility justify practices praising and blaming by pointing to their effects on the development our reasons-responsive capacities. Exercising these capacities has instrumental value—for example, they enable agents act rightly flourish—but some argue that it is also intrinsically valuable. In this paper, I develop a value theory morally responsible agen...

The following article may serve as a learning tool for chaplains who are available to provide care servicewomen suffering from moral injury. Moral injury occurs when someone experiences, takes part in, or witnesses traumatic event that violates their deeply held beliefs about truth, justice, morality. Using gendered approach rooted in feminist principles and research, the text provides list of ...

While online harassment is recognized as a significant problem, most scholarship focuses on descriptions of and its effects. We lack explanations why people engage in beyond simple bias or dislike. This article puts forth an explanatory model where networked social media functions mechanism to enforce order. Drawing from examples taken qualitative interviews with who have experienced ( n = 28) ...

This paper describes a method for identification of the informative variables in the information system with discrete decision variables. It is targeted specifically towards discovery of the variables that are non-informative when considered alone, but are informative when the synergistic interactions between multiple variables are considered. To this end, the mutual entropy of all possible k-t...

There is an increasing interest in the machine learning community to automatically learn feature representations directly from the (unlabeled) data instead of using hand-designed features. The autoencoder is one method that can be used for this purpose. However, for data sets with a high degree of noise, a large amount of the representational capacity in the autoencoder is used to minimize the ...